jupyter_best_practices_part_1.ipynb

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  "metadata": {
    "colab": {
      "name": "jupyter-best-practices-part-1.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/martin-fabbri/colab-notebooks/blob/master/jupyter_best_practices_part_1.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "M2zBp-zwzLik",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import datetime as dt\n",
        "import matplotlib.pylab as plt"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "J_Qp8mXqI9R-",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 201
        },
        "outputId": "2126d8ce-e9b3-44cc-8a9d-7667d10f27e1"
      },
      "source": [
        "dataset_url='https://raw.githubusercontent.com/martin-fabbri/colab-notebooks/master/data/wowah_data.csv'\n",
        "df = pd.read_csv(dataset_url)\n",
        "df.head()"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>char</th>\n",
              "      <th>level</th>\n",
              "      <th>race</th>\n",
              "      <th>charclass</th>\n",
              "      <th>zone</th>\n",
              "      <th>guild</th>\n",
              "      <th>timestamp</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>59425</td>\n",
              "      <td>1</td>\n",
              "      <td>Orc</td>\n",
              "      <td>Rogue</td>\n",
              "      <td>Orgrimmar</td>\n",
              "      <td>165</td>\n",
              "      <td>01/01/08 00:02:04</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>65494</td>\n",
              "      <td>9</td>\n",
              "      <td>Orc</td>\n",
              "      <td>Hunter</td>\n",
              "      <td>Durotar</td>\n",
              "      <td>-1</td>\n",
              "      <td>01/01/08 00:02:04</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>65325</td>\n",
              "      <td>14</td>\n",
              "      <td>Orc</td>\n",
              "      <td>Warrior</td>\n",
              "      <td>Ghostlands</td>\n",
              "      <td>-1</td>\n",
              "      <td>01/01/08 00:02:04</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>65490</td>\n",
              "      <td>18</td>\n",
              "      <td>Orc</td>\n",
              "      <td>Hunter</td>\n",
              "      <td>Ghostlands</td>\n",
              "      <td>-1</td>\n",
              "      <td>01/01/08 00:02:04</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2288</td>\n",
              "      <td>60</td>\n",
              "      <td>Orc</td>\n",
              "      <td>Hunter</td>\n",
              "      <td>Hellfire Peninsula</td>\n",
              "      <td>-1</td>\n",
              "      <td>01/01/08 00:02:09</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    char   level  race  ...                zone  guild          timestamp\n",
              "0  59425       1   Orc  ...           Orgrimmar    165  01/01/08 00:02:04\n",
              "1  65494       9   Orc  ...             Durotar     -1  01/01/08 00:02:04\n",
              "2  65325      14   Orc  ...          Ghostlands     -1  01/01/08 00:02:04\n",
              "3  65490      18   Orc  ...          Ghostlands     -1  01/01/08 00:02:04\n",
              "4   2288      60   Orc  ...  Hellfire Peninsula     -1  01/01/08 00:02:09\n",
              "\n",
              "[5 rows x 7 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5vFQQSQZku6J",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 70
        },
        "outputId": "440fca0d-eff4-4113-a0da-6a5a17a297ec"
      },
      "source": [
        "def loggg(f):\n",
        "  def wrapper(df, *args, **kwargs):\n",
        "    tic = dt.datetime.now()\n",
        "    result = f(df, *args, **kwargs)\n",
        "    toc = dt.datetime.now()\n",
        "    n_char = result.groupby('char').agg(n_char=('char', np.size)).shape\n",
        "    print(f'{f.__name__} took: {toc - tic} shape={result.shape} n_char={n_char[0]}')\n",
        "    return result\n",
        "  return wrapper\n",
        "\n",
        "@loggg\n",
        "def start_pipeline(df):\n",
        "  return df.copy()\n",
        "\n",
        "@loggg\n",
        "def clean_dataset(df):\n",
        "  df.columns = [col_name.lstrip() for col_name in df.columns ]\n",
        "  return df\n",
        "\n",
        "@loggg\n",
        "def remove_outliers(df):\n",
        "  return df\n",
        "\n",
        "clean_df = (df\n",
        " .pipe(start_pipeline)\n",
        " .pipe(clean_dataset)\n",
        " .pipe(remove_outliers))"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "start_pipeline took: 0:00:00.037775 shape=(1606208, 7) n_char=9466\n",
            "clean_dataset took: 0:00:00.000184 shape=(1606208, 7) n_char=9466\n",
            "remove_outliers took: 0:00:00.000012 shape=(1606208, 7) n_char=9466\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oCuZotCurbYb",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 70
        },
        "outputId": "2430b869-4f9b-4c36-9bbd-9b4aee6f104f"
      },
      "source": [
        "df.columns\n"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['char', ' level', ' race', ' charclass', ' zone', ' guild',\n",
              "       ' timestamp'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XmbXgc2uI9O5",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "a39ea945-e084-4547-ca1b-89dfafa50ca6"
      },
      "source": [
        "df.columns = [col_name.lstrip() for col_name in df.columns ]\n",
        "df.columns"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['char', 'level', 'race', 'charclass', 'zone', 'guild', 'timestamp'], dtype='object')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vnpIdKE_I9LR",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 232
        },
        "outputId": "9090949e-bf0f-496b-8b16-5d857103a4da"
      },
      "source": [
        "df2 = (df\n",
        " .groupby('char')\n",
        " .agg(n_row=('level', np.size),\n",
        "      min_level=('level', np.min),\n",
        "      max_level=('level', np.max),\n",
        "      guild=('guild', np.max)))\n",
        "df2.head()"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>n_row</th>\n",
              "      <th>min_level</th>\n",
              "      <th>max_level</th>\n",
              "      <th>guild</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>char</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>231</td>\n",
              "      <td>54</td>\n",
              "      <td>60</td>\n",
              "      <td>282</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>943</td>\n",
              "      <td>70</td>\n",
              "      <td>70</td>\n",
              "      <td>79</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>895</td>\n",
              "      <td>69</td>\n",
              "      <td>70</td>\n",
              "      <td>65</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>217</td>\n",
              "      <td>70</td>\n",
              "      <td>70</td>\n",
              "      <td>205</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>17</td>\n",
              "      <td>62</td>\n",
              "      <td>62</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "      n_row  min_level  max_level  guild\n",
              "char                                    \n",
              "7       231         54         60    282\n",
              "9       943         70         70     79\n",
              "19      895         69         70     65\n",
              "21      217         70         70    205\n",
              "22       17         62         62      5"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "i928VEUmI9Hr",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 232
        },
        "outputId": "e0660ef3-486d-4dd0-dba6-032fd7e49ec3"
      },
      "source": [
        "df3 = (df.groupby('guild').agg(n_char=('char', 'nunique')))\n",
        "df3.head()"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>n_char</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>guild</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>-1</th>\n",
              "      <td>6931</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>21</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>229</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       n_char\n",
              "guild        \n",
              "-1       6931\n",
              " 1          1\n",
              " 3         21\n",
              " 4         18\n",
              " 5        229"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1F9D6J51VipP",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 201
        },
        "outputId": "efa89cf9-091a-45e3-d047-51e30ede210b"
      },
      "source": [
        "df4 = df2.merge(df3.reset_index())\n",
        "df.head()"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "\n",
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              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>char</th>\n",
              "      <th>level</th>\n",
              "      <th>race</th>\n",
              "      <th>charclass</th>\n",
              "      <th>zone</th>\n",
              "      <th>guild</th>\n",
              "      <th>timestamp</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>59425</td>\n",
              "      <td>1</td>\n",
              "      <td>Orc</td>\n",
              "      <td>Rogue</td>\n",
              "      <td>Orgrimmar</td>\n",
              "      <td>165</td>\n",
              "      <td>01/01/08 00:02:04</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>65494</td>\n",
              "      <td>9</td>\n",
              "      <td>Orc</td>\n",
              "      <td>Hunter</td>\n",
              "      <td>Durotar</td>\n",
              "      <td>-1</td>\n",
              "      <td>01/01/08 00:02:04</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>65325</td>\n",
              "      <td>14</td>\n",
              "      <td>Orc</td>\n",
              "      <td>Warrior</td>\n",
              "      <td>Ghostlands</td>\n",
              "      <td>-1</td>\n",
              "      <td>01/01/08 00:02:04</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>65490</td>\n",
              "      <td>18</td>\n",
              "      <td>Orc</td>\n",
              "      <td>Hunter</td>\n",
              "      <td>Ghostlands</td>\n",
              "      <td>-1</td>\n",
              "      <td>01/01/08 00:02:04</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2288</td>\n",
              "      <td>60</td>\n",
              "      <td>Orc</td>\n",
              "      <td>Hunter</td>\n",
              "      <td>Hellfire Peninsula</td>\n",
              "      <td>-1</td>\n",
              "      <td>01/01/08 00:02:09</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    char  level race charclass                zone  guild          timestamp\n",
              "0  59425      1  Orc     Rogue           Orgrimmar    165  01/01/08 00:02:04\n",
              "1  65494      9  Orc    Hunter             Durotar     -1  01/01/08 00:02:04\n",
              "2  65325     14  Orc   Warrior          Ghostlands     -1  01/01/08 00:02:04\n",
              "3  65490     18  Orc    Hunter          Ghostlands     -1  01/01/08 00:02:04\n",
              "4   2288     60  Orc    Hunter  Hellfire Peninsula     -1  01/01/08 00:02:09"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ybXLXogMVimT",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 725
        },
        "outputId": "7c5fc763-88f3-477b-bbc9-8ca07e3ad6c9"
      },
      "source": [
        "plt.scatter(x=df4['n_row'], y=df4['level_inc']);"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "error",
          "ename": "KeyError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m   2896\u001b[0m             \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2897\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2898\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
            "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
            "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
            "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
            "\u001b[0;31mKeyError\u001b[0m: 'level_inc'",
            "\nDuring handling of the above exception, another exception occurred:\n",
            "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-7-e1d645c8e783>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mscatter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdf4\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'n_row'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdf4\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'level_inc'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m;\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   2993\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnlevels\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2994\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_multilevel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2995\u001b[0;31m             \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2996\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mis_integer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2997\u001b[0m                 \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m   2897\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2898\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2899\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_maybe_cast_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2900\u001b[0m         \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmethod\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmethod\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtolerance\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtolerance\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2901\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mindexer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mndim\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m1\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mindexer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msize\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
            "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
            "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
            "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
            "\u001b[0;31mKeyError\u001b[0m: 'level_inc'"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PDztIxhHVije",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "df4['level_inc'] = df4['max_level'] - df4['min_level']"
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}